Promoting Branding Of Food Products Commerce Essay


Store brand products[1] are owned and branded by distributors or retailers whose primary economic commitment is distribution as opposed to production (Richardson, Dick, & Jain, 1994; Schutte, 1969). In recent years, the role and importance of store brands have increased significantly in the market. Among retail brand products, grocery product dominates the market (Baltas, 1997).

From being low priced second class products serving the less fortunate, store brands today have become more appealing to consumers who seek quality products at reduced prices (Prendergast & Marr, 1997). Consumers are able to select a wider variety of store brand products from various categories, including household electronics, wine, and organic food.

Today, store brands have become a competitive advantage in the battle waged between retailers and manufacturers over channel control and consumer loyalty (Patti & Fisk, 1982). In a number of countries, some product categories have already been dominated by store brands (Baltas, 1997, 2003; Dick, Jain, & Richardson, 1995). Not only can retailers enjoy higher sales and gross margins from store brand products, several studies also indicated that retailers can use them to increase retail power against manufacturers, increase shelf control and enhance store loyalty.

Lady using a tablet
Lady using a tablet


Essay Writers

Lady Using Tablet

Get your grade
or your money back

using our Essay Writing Service!

Essay Writing Service

A global study published in September 2005 (Nielsen, 2005) reveals that Singapore itself is one of the ten fastest growing store brand markets in the grocery sector. As of 2005, the store brands in Singapore have a value share of 3%, and the market is continuously growing at a rate of 16% a year (Nielsen, 2005). Manufacturer growth, in contrast, only managed to reach a growth rate of 1% per year. The growth and penetration of store brand sales in the local market is rapid and is expected to continue. Furthermore, the current economic slowdown and recession help create a more favorable environment for store brands. Quelch and Harding (1996) suggest that store brand performance is associated with the current economic condition. A consumer research report published by Private Label Manufacturers Association (2009) also showed that nearly 75% of the respondents agreed that recession is an important factor which hinders their decision-making process when buying store brands. Generally, the market share and popularity of store brands increase when there is an economic downturn. The consumer panel data collected by Nielsen (2009) also revealed that 91% of households in Singapore purchased at least some store brand products for six months between June and November 2008. With that, it is apparent that these consumers have accepted store brands in the local marketplace extensively.

In view of the great potential store brands have in the local market, well-organized large retail chains have expanded their line of store brand products more aggressively in the recent years. Despite lower prices, quality guarantees, and more effective marketing communications, the main problem that marketers of store brands face is that consumers still prefer manufacturer brands over store brands, if the price is right (Shapiro, 1993). Therefore it is important for retailers to identify and understand the consumers' perceptions and preferences of their store brands.

1.2 Research Objectives

Based on previous research, different factors have been found to affect how consumers perceive and purchase store brand products. A number of previous studies have examined the demographics and socio-economic characteristics of store-brand buyers (e.g. Frank & Boyd, 1965). Other studies have focused on the effects of product-related factors affecting perception and demand of store brand products (e.g. Bellizzi, Krueckeberg, Hamilton, & Martin, 1981; Dick et al., 1995). Among these factors, brand name was found to be the most dominant aspect in influencing consumers' perception and preference of a product (e.g. Brady, Bourdeau, & Heskel, 2005; Sullivan, 1998).

Despite that, very few research studies have focused on comparing consumers' perception, preference and buying behaviour between different specific store brands. Given the fact that consumers from different parts of the world have different perception of store brand products, it shows that store brands and country specific researches are needed. Henceforth, the current experiential study will be conducted in Singapore where specific store and manufacturer brands exist.

Leveraging on the previous studies, the purpose of the current study is to find out how consumers, who assess base on brand cue only, evaluate products of manufacturer and store brands across different product categories. The current research also aims to find out the effect of these brand names (i.e. manufacturer brands and store brands) on consumers' perception and preference towards different product categories. Additionally, this study is also aspired to discover how demographics affect the way consumers view store brands.

Lady using a tablet
Lady using a tablet


Writing Services

Lady Using Tablet

Always on Time

Marked to Standard

Order Now

By comparing the existing products in the market, it is challenging to analyze how brand names affect consumers' perception and preference as most products with different brand names have different physical attributes (Sullivan, 1998). Hence, it is difficult to isolate the effect of brand names from that of other attributes such as price and packaging. To overcome these difficulties, current studies employed a full factorial (3 brands x 4 products) conjoint analysis.

1.3 research scope

In order to understand the effect of brand name on consumers' perception and preference towards different product categories, the interviewer administrated survey with 150 respondents was conducted. These respondents are selected through suitable sampling and are required to have visited both FairPrice and Cold Storage supermarkets within the past three months. The data collected is measured through reliability test, conjoint analysis, ANOVA analysis, t-test and Pearson's R correlation coefficient.

1.4 Structure of Dissertation

The rest of the research paper is organized as follows. Firstly, it will begin with an in-depth review of current literatures available, in relation to the topics and concepts that are in scope of current studies. The research paper will then present a description of the research methodology, which continues on with the findings and analysis. The final section discusses research ideas, conclusion and limitations of the study, as well as providing directions for future research.

chapter two:


This section will cover what has been achieved from store brands-related research to date. Information has been gathered from various sources such as journal articles, news articles and news articles. The scope of literature review includes: factors influencing consumers' perception and preference towards store brand product, in particularly on consumer-related and product-related factors, and the effect of brand name on product evaluation.

2.2 Perceived Risk

When choosing among competing brands, consumers are likely to purchase the brand with the least perceived risk. As Sethuraman and Cole (1999) defined: “perceived risk arises from consumers' perception about the magnitude of the adverse consequences and the probabilities that these consequences may occur if the store brand is purchased”. Consumers are faced with tough decisions when buying products. There are various brands to choose from, and different levels of involvement associated. Consumers have to determine the value, that is, the gains or losses they would get from the various choices available before making a decision.

Risks that are associated with the purchase of a product have been categorized into different groups by different authors. Although risk can be of many types (i.e. performance, financial, social, time, and safety), Semeijin, Riel and Ambrosini (2004) argued that performance and physical risks were most closely related with the store brand/manufacturer brand choice. Performance risk is defined as the performance consequences of a product failure, and to the probability that these consequences will occur (Semeijn et al., 2004). Physical risk, in this case, refers to the probability of a purchased product having some physical defect. They (2004) commented that a product of poor performance (quality) standards is prone to physical damage. It is therefore essential to understand how consumers perceive the product quality of store brands, so that retailers can further improve on their strategies. Henceforth, current studies will leverage on the concept perceived performance and physical risk to develop a questionnaire that is suitable for the research.

2.3 Cue utilization theory

As mentioned, consumers are faced with uncertainty of product performance and quality when choosing among competing brands. There are instances that some consumers prefer store brands to manufacturer-brands (Burton, Lichtenstein, Netemeyer, & Garretson, 1998), either due to cost savings associated with more affordable prices, or because they do not perceive differences in quality between store and manufacturer brands (Narasimhan & Wilcox, 1998). Still, there are many consumers who do not share this perspective. Despite the assurance of the Private Label Manufacturers' Association that store brands offer the same quality as manufacturer brands, studies (e.g. Bellizzi et al., 1981; Szymanski & Busch, 1987) have shown that differences does exist in quality perception between them. In most situations, store brand products are perceived to be inferior when compared to products of manufacturer-brands.

Many of the time, consumers rely on a number of evaluative cues to reduce perceived risk when assessing quality across competitive products. Dawar and Parker (1994) identified five reasons for the use of cues:

  1. perceived risk would be required to be reduced by the consumer (Olson, 1976);
  2. the consumer lacks of expertise and ability to assess quality (Rao & Monroe, 1988);
  3. consumer involvement is low (Celsi & Olson, 1988);
  4. objective quality is too complex to assess or the customer does not have the habit of spending much time doing such assessments (Allison & Uhl, 1964); or
  5. there is preference for information search (Nelson, 1970)(Nelson, 1970, 1974).
Lady using a tablet
Lady using a tablet

This Essay is

a Student's Work

Lady Using Tablet

This essay has been submitted by a student. This is not an example of the work written by our professional essay writers.

Examples of our work

A cue is defined as “a characteristic event, quality, or object that is external to the consumer that is encoded and used to categorize a stimulus object” (Crane & Clarke, 1988). According to the Cue utilization theory, products consist of a range of cues that serves as surrogate indictors of quality to consumers (Olson, 1972). Cues can be categorized into two groups - extrinsic and intrinsic (Olson, 1972). Extrinsic cues represent product-related attributes that are not part of the physical products - including brand name, price and packaging. On the other hand, intrinsic cues are product-related attributes, such as ingredient, taste and texture, which cannot be manipulated without changing physical properties of the product (Richardson et al., 1994).

Consumers, for several reasons, judge quality by using extrinsic cues only. One of the reasons is that intrinsic cues are not available at the point of purchase. Furthermore, evaluation of intrinsic cues requires more time and effort than is perceived as worthwhile (Fred, 1993). Last but not least, consumers may not be equipped with the knowledge to evaluate product quality using intrinsic cues. Instead, they make quality judgment by using extrinsic cues as they are easily assessed, evaluated and interpreted (Kara, Rojas-Méndez, Kucukemiroglu, & Harcar, 2009).

In the last decade, the amount of research focused on extrinsic cues has grown significantly. These studies concentrated on cues such as brand name (Akerlof, 1970; Darby & Karni, 1973), product feature or packaging (Nelson, 1970; Olson, 1976), and price (Berry & Yadav, 1996; Olson, 1972, 1976; Rao & Monroe, 1989; Wolinsky, 1983).

Several studies have concluded that one of the crucial reasons for consumers to perceive store brands as inferior is due to the price perceived-value relationship (Monroe & Dodds, 1988; Olson, 1976). Rao and Monroe (1988), for instance, discovered that price and perceived quality displays a positive and significant relationship for consumer products. Many consumers use price as a measurement of value and quality (Dickson & Sawyer, 1990). Higher-priced products are believed to be of higher quality. Hence, store brands, which are approximately 10% to 30% cheaper than manufacturer-brands in the grocery product classes, are perceived to be of lower quality (Baltas, 1997).

Lichtenstein & Burton (1989), however, suggested that the price-value relationship might not be accurate in assessing product quality. This philosophy was further supported by Davies and Brito (2004). In their study, they observe those who buy Kellogg's cornflakes on a regular basis, only 38% of the respondents prefer the brand over two other store brands during a blind test. Nevertheless, they concluded that brand image was the reason why consumers were willing to pay a premium for products of manufacturer brands. With contradicting arguments among previous studies, this leads to the first hypothesis:

Along with other research findings, brand name was found to be more important cue than price and physical appearance when evaluating product quality (Jacoby, Szybillo, & Busato-Schach, 1977; Rao & Monroe, 1989). Generally, the relative importance of these cues follows their specificity, or the extent to which a particular cue is not shared among competitive products (Dawar & Parker, 1994). Taking a brand name as an example, it is usually shared by only a few products within a category of competitive products and is therefore a significant cue. Conversely, price and packaging can be shared to a greater extent among competing products, so they are less significant. The more significant a cue is, the more likely it is used in assessing the quality of product.

2.4 The effect of brand name on product evaluation

Previous studies have reported that brand names possess the ability to aid consumers in recalling important product information. A brand is a name, term, sign, symbol, or design, or a combination of them, intended to identify the source of a product and differentiate the product from its competitors' (Kotler, 1991). In the current study, brand equity refers to the consumer based brand equity, where Farquhar (1989) defined it as the value endowed by the brand to the product. Lassar, Mittal, and Sharma (1995) identified five key considerations, brand equity:

  1. refers to consumer perception, instead of objective indicators;
  2. is an association of a global impression of the value with a brand;
  3. is developed from the brand name, as well as, the physical aspects of the brand;
  4. is a relative measure, that have to be compared to direct competitors; and
  5. influences the financial performance of the brand positively.

Symbolic in origin, brands usually suggested a definite image involvement. In such competitive environment, this visual environment is even more vital, considering consumers' shifting loyalties, brands need to struggle for their position and plain brand names may not be adequately strong. A brand can boost the demand for a product in many ways. Brands offer vital data by escalating responsiveness and dish up as an important determinant for quality (Sullivan, 1998).

Brand awareness refers to consumer's capability to recognize the brand under different situations (Keller, 1993) and is regarded to be of particular importance in low involvement product categories (Keller, 1993; Ritson, 2003). When it comes to high involvement products, such as cars, consumers are likely to spend more time on the decision making process and make effort to learn about unfamiliar brands (Ritson, 2003). Groceries, in general, can be considered as low involvement products (Anselmsson, Johansson, & Persson, 2007). Brand names of groceries can influence the type of products that potential consumers would consider in their search process in grocery stores. Consumers might depend on brand names as a proxy for quality in their decision making process, as some aspects of the products would not be understood until it is purchased and consumed. Hence, it is essential to understand the perception consumers have towards different brands, which will be studied in the current research.

Brand equity, as mentioned, is closely associated with the perceived quality of a product. Previous studies have reported that brand names used by consumers to represent a composite of information about the attributes that truly determine quality (Olson, 1976; Osselaer & Alba, 2000). Moreover, it also possesses the ability to aid consumers in recalling important product information. Therefore, not only should the brand be renowned, but also known for something that is valuable to the consumers. Janiszewski & Osselaer (2000), for instance, identified that the association from a brand name to a product benefit allows consumers to recognize a product's positioning, and the association from a brand name to a product category helps consumers to understand potential usage situations. As cited from DelVecchio (2001), he commented that:

“Private label brands typically follow a low-cost strategy. By keeping advertising and promotion costs low, retailers hope to pass cost savings onto consumers. The strategy undertaken by private label brands results in sizeable discrepancies between the marketing communications budgets of private label and national brands.”

Given that brand equity is mainly built through marketing communication campaigns, manufacturer brands are usually higher in equity and perceived quality as compared to store brands. Therefore, when consumers reply on brand equity as quality cue, they are often more motivated to purchase products of manufacturer brands (Livesey & Lennon, 1978; Richardson, Jain, & Dick, 1996)

The brand image of a product can also influence demand. Reduction of cognitive effects required in making buying decision was displayed in an experimental research which showed that brand names would help consumers assess product quality (Boush et al., 1987). Store brand products are often perceived to be of inferior quality than manufacturer branded goods. It would appear that consumers prefer the guarantee that a well-known manufacturer brand brings, rather than the risks associated with buying from store brands when in search of a product competing amongst each other. In addition, a theoretical model developed by Landes and Posner (1987) revealed that consumers are willing to pay more for brands that reduce search costs. In many cases, even with similar quality, some consumers still will pay more for manufacturer brands, seeing that they possess a more appealing brand image. With specific geographical focus, the current research will therefore examine the influence of brand name on product perception and preference specifically in the Singapore context.

Apart from product-related factors, it is also essential to understand some of the consumer-related factors that influence consumers' perception towards store brand products. The following section of the literature review will be touching on this area.

2.1 Demographics affecting how consumers perceive store brands

Since the 1960s, there have been many research studies focusing on store brands. Initially, research was focused on socio-economic consumer characteristics (Burger & Schott, 1972; Frank & Boyd, 1965). However, subsequent studies have gradually moved towards other aspects, including product-related factors that affect consumers' perception of store brand (e.g. Lybeck, Holmlund-Rytkönen, & Sääksjärvi, 2006)brand loyalty and store loyalty (e.g. East, Harris, Willson, & Lomax, 1995).

Several studies examining the characteristics of the store brand buyer have also attempted to investigate whether the tendency to buy store brands is associated with demographic or socio-economic consumer characteristics. However, the findings were rather weak and insignificant. One of the earliest published studies by Frank and Boyd (1965) discovered some indications that buyers of store brand products are older, better educated and have lower income than buyers of manufacturer brand products. Likewise, Burger and Schott (1972) found that store brand buyers have higher education. Coe (as cited in Lybeck et al. (2006) and Murphy (1978), in contrast, pointed out that store brands buyers belong to higher rather than lower income groups. All in all, the findings from previous research are rather inconclusive and insufficient to distinguish between store and manufacturer brand consumers (Lybeck et al., 2006). When compared with consumer type, Dhar and Hoch (1997), Livesey and Lennon (1978), and Yelkur (2000) state that product category is more appropriate in explaining perception and preference. This is what the current research explores with its focus on four different product categories.

Although several studies had been undertaken to investigate the characteristics of store brand buyers, most of these studies were conducted in the 1960s and 1970s, and variables may therefore be outdated. Moreover, none of the work has been done using data from Singapore. Most related research findings were based on the USA which exhibited a different socio-economic and retail environment (Baltas, 2003).

In the last decade, there were evidences showing that store brands were becoming more popular as consumers had greater trust in the quality of these products (Baltas, 1997)). The changing perception might be caused by the increased emphasis that retailers/distributors placed on quality control process to maintain and improve the quality of store brand products.

According to a study published by Private Label Manufacturers Association (2009), nearly one-third of the consumers have increased their store brand purchasing. In Singapore, there is an increasing number of middle and high income households making the switch to these cheaper alternatives in the wake of the deepening recession (Nielsen, 2009). Base on the Nielsen Retail Index, there was a growth of 14.3% in the sales of store brands for the six months which ended in April 2008, compared with 6.2% for the sales of manufacturer brands.

Together with previous inconclusive findings, this is the gap that the current study attempts to fill, at least partially, discovering the characteristics of buyers between competing manufacturer-brand and store brands in the Singapore context.

To summarize, a variety of different factors have been found to influence how consumer perceive and purchase store brand products. Brand name is found to be more of an important cue when evaluating product quality. The theoretical literature has also provided insights on the effect of brand names and product categories on consumers' perception, preference and demand. In addition, this information also supports the purpose of the current study: to examine the effect of brand names on consumers' perception and preference towards different products. Before going into the research hypothesis, survey and its findings from Singapore on how brand names affect consumers' preference and demand for store brand products, the Singaporean market is briefly discussed.

2.5 The Store brand Market in Singapore

Globally, both manufacturer brand and store brand companies strive to acquire a better understanding of the retail-brand demand characteristics. Likewise, it also applies to Singapore where extremely little of such research has been carried out. Current studies focus on the Singaporean market where store brands are constantly gaining market shares in the recent years.

Overall, store brand products in Singapore are not as developed as those in the West. The market share of store brands in grocery outlets in Singapore is approximately 2%, whilst in the USA it is roughly around 20%, and varies between 20% and 40% in the European countries (Nielsen, 2005).

The first branded store grocery products appeared in Singapore in the mid 1980s, by NTUC FairPrice. A decade ago, store brand product categories in Singapore consisted of nothing but commodities such as tissue paper, sugar, and rice. Considering the great potential of store brands, large retail chains have started to expand their line of store brand products recently. Since then, NTUC FairPrice has emphasized on expanding its collection of store brands products from about 800 to over 2,000 items in 2008 under its FairPrice and Pasar brands. The store brands products are priced at approximately 10% to 15% lower than products of manufacturer brands, and make up about 20% of the total product offerings (Liang, 2009). The changed consumer perception of private label quality, in addition to the economic recession, boosted the performance of NTUC FairPrice. With more than 200 outlets across Singapore, NTUC FairPrice continued to maintain its position as a market leader (Euromonitor International, 2010). In 2009, the retailer was ranked first in Singapore's supermarket channel, with a 46.3% retail value share.

Cold Storage, another leading retailer, also has its store brands - First Choice and No Frills. As of 2008, there are more than 1,600 store brand products. The retailer offers a wide variety of store brand products with close to 40 categories from dairy, snacks, wines, breads and cereals, rice & noodles, fresh squeezed juice to wines to drinks, frozen, household, paper goods, and kitchenware . Like other store brand products, products of First Choice and No Frills are priced around 10% to 15% cheaper than other branded offerings from leading manufacturers. With 37 outlets across the island, Cold Storage managed to achieve a value share 9.8% in 2009.

Other supermarket retailers that own their own store brands include Giant hypermarket, Shop N Save, and Sheng Shiong supermarket. Both Giant and Shop N Save carry an adequate amount of store brand products in their outlets. Whist for newcomer of store brand - Sheng Shiong Supermarket only became active in expanding their line of store brand products during the second half of 2007. Currently, the supermarket is still at the early stage of developing and expanding the product range under its store brand. As of 2009, the retailer carried only a limited number of store brand products.

chapter three:


The current work will collect quantitative data by questionnaire to obtain useful findings to achieve the objectives stated. This survey was designed to capture the impression resulting from a product evaluation on three product attributes (dependent variables) and the two independent variables of brands and product categories (see Table). A three (brand names) by four (products) full factorial design was employed to test the hypotheses with brand names between product attributes within each product category.

3.1 hypotheses

Cue utilization studies provide a framework through which would examine possible causes of consumers' perceptions of manufacturer and store brand grocery products. Most of the time, consumers rely on extrinsic cues to evaluate product quality. With lower prices, poorer packaging, less advertising, and lack of strong brand recognition, store brands are often less appealing than manufacturer-brands, store brands suffer from deficiencies relative to manufacturer-brands (Richardson et al., 1994). Brand cue, as mentioned, has been discovered to be the most important extrinsic cue to assess product quality (e.g. Jacoby et al., 1977; Rao & Monroe, 1989). Moreover, it facilitates choice making when competitive products are either too similar to be easily differentiated or when they cannot be seen (Herbig & Milewicz, 1993; Hoch & Ha, 1986; Olson, 1972). Henceforth, this leads to the second hypothesis:

H1: When assessing with brand cue only, products of manufacturer brands will receive the highest evaluation as compared to those from store brands.

Bulks of studies showed that consumers perceived that store brands are of inferior quality than manufacturer-brands (e.g. Richardson et al., 1994; Shapiro, 1993). Despite that, many made little effort to compare consumers' perception between two store brands. Nevertheless, the findings of non-significant store brand treatment effect indicated that store brands are regarded as comparable in terms of quality (Richardson et al., 1994; Richardson, 1997). To obtain a better understanding of consumers' perception towards store brands, the current study hypotheses that:

H2: When assessing with brand cue only, products from store brands will receive the same evaluation.

As mentioned by Thompson (1999), consumers, who have a negative impression with one product category, are less likely to purchase store brands in other categories. With that, it leads to the third hypothesis:

H3: Product categories will not influence consumers' evaluation on the three attributes.

Suffering from brand cue inadequacies, Consumers' dependence on brand cue in product quality assessment presents retailers of store brands with a hitch. Retailers will usually price store brand products 15% to 37% lower than manufacturer brands in order to encourage the purchase of these products (Shapiro, 1993). As the lower priced would serve only to exacerbate further unfavorable quality perceptions, it is ironic that consumers rely on brand cue in the evaluation of product quality. Most retailers emphasize on a different aspect to market their store brand lines to overcome this problem (Richardson et al., 1994). In short, instead of competing directly with the manufacturer brands on the basis of quality, these retailers have chosen a ‘value for money' approach in the marketing of their store brand lines (K. Davies, Gilligan, & Sutton, 1986; Martell, 1986; Ody, 1987).

Value for money involves a price-perceived quality trade-off (Livesey & Lennon, 1978; Myers, 1967). In one of the previous studies, Richardson et al. (1994) stated that:

“By taking a value for money orientation in the marketing of their store brands, retailers hope to instill the purchase of these products not only from those consumers who perceive that store brands are lower priced but of relatively good quality and also from those consumers who perceive that store brands are lower priced and of relatively bad quality as long as saving associated with the price differential provide. In fact, Myers (1967) found that the latter segment of the market (lower price, lower quality) constitutes 48% of the store brand clientele whereas the former segment (lower price, same quality) comprises only 23% of store brand buyers.” (p. 30)

With that, it leads to the fourth hypothesis:

H4: Perceived value for money of store brands is more strongly correlated with consumer willingness to buy store brands than its perceived quality.

3.2 Product/category selection

With the increasing number of competitors in the markets, retailers need to assess their strategies carefully, so as to gain market shares. Semeijn et al. (2004) suggested that developing a strong store brand can play an important role in this effort. While a store brand can be very successful in some product categories, it can also be ineffective in others. The differentiations among product categories seem to cause variance in store brand shares both across markets and retailers (Dhar & Hoch, 1997).

In view of retailers, there are numerous types of risks associated with the development of new products under a store brand. Store brand, also known as umbrella brands, are brands that include a number of different product categories (Semeijn et al., 2004). Consumers who have negative experiences with one product category, have been found by Thompson (1999) to be less likely to purchase store brands in other categories. On top of that, unpleasant encounters may erode consumers' confidence towards the store as a whole. It is therefore important for retailers to assess the likelihood of acceptance of a new category under the store brand. This assessment can be made by examining consumers' perception of store brands and measurement how various product categories affect their evaluation of store brands.

Groups of identical products, which possess same attributes but with different brand names, will serve as the basis of an experiment to examine how brand names affect preference and demand. Due to the nature of the experiment, all products tested are not real. Leveraging on that, the current study can use product categories where the local retailer have yet to develop. This will allow local retailers to discover categories of products that have the potential to be launched in the local market.

According to a study conducted by Nielsen (2005), the top five product categories that dominate the global grocery private-label market include aluminum foil (49%), complete ready meals (47%), milk (43%), garbage/refuse bags (40%), and meat/poultry/game (39%). The study has also listed the top ten fastest growing store brand product category, for example drinking yogurt with a growth rate of 28%, baby food (20%), complete ready meal (14%), and chocolate (13%) respectively. Of those, there are also a number of product categories that have yet to be launched by local retailers. Henceforth, the product categories used in the case study were selected based on the fastest growing product categories in the global market that have not been developed by Singapore retailers in the market. On top of that, the need for evaluating different product classes will further guide the current research in selecting the product categories.

Four different groups of product categories are chosen, including fresh semi-refined groceries, frozen ready meals, shelf stable products and confectionary products. When the degree of refining, degree of freshness, and category penetration are considered, these four groups can be used to represent the total variety of products categories in grocery stores. This allows the present study to examine the perception and preferences of consumers towards store brands, in general.

In the case of the current research, each group will be represented with one product category. The followings are four product categories that will be tested:

  1. Fresh semi-refined groceries: Drinking yogurt
  2. Frozen ready meals: Lasagna- ready meal
  3. Shelf stable products: Peanut butter
  4. Confectionary products: Chocolate bar

3.3 Brand Selection

There are three brands allocated to each of the product category. As the focus of the current research is on store brands, two out of the three brands will be permanently represented by competitive store brands - FairPrice and First Choice. Currently, FairPrice and Cold Storage are dominating the Singapore grocery market. Although there are more than one store brand within each organisation, FairPrice (from FairPrice) and First Choice (from Cold Storage) are the core brands that the retailers carry. There are at least 1,600 different products named under these store brands, hence it will be interesting to find out the perception and preference of what consumers have towards them.

The selection of manufacturer brand is based on two criteria. Firstly, the manufacturer brands chosen are the market leaders of the respective product categories. Secondly, manufacturer branded products must be available at both FairPrice and Cold Storage. This is to make sure that the brands have equal exposure to respondents who are participating in the present research. After consultation with retail managers, the following four manufacturer brands were selected for the experiment:

  1. Drinking yogurt: Marigold
  2. Lasagna- ready meal: SunShine
  3. Peanut butter: Skippy
  4. Chocolate bar: KitKat

3.4 sample and administration

The sample comprised of 150 local consumers who visited both FairPrice and Cold Storage supermarkets within the past three months, ages between 15 years and 60 years. The sampling method used was convenience sampling because it is quick and economical, where large number of responses can be gathered in a short period of time. Due to the complexity of the experiment, it had to be an interviewer-administrated survey session, where an interviewer was present to guide, prompt and encourage respondents to answer the questions. Furthermore, it aided in decreasing the probability of non-response error.

3.5 Procedure

Four product categories, as mentioned, would be used in the current research. Once a respondent agreed to participate in the survey, he or she would be showed a total of 12 display boards in random order. A picture and relevant information of a product prototype will be exhibited on each display board. The information indicated would include brand name, size, price and ingredients used. Other than the brand logo, everything will remain the same (control all other variables) in each of the category. Figure X shows an example of the display board. While viewing each display board, respondents would be required to answer 10 questions (for three dependent measures). This process would be repeated for each display board so that across all respondents, all four categories of products would be viewed in comparison to the three brands (Manufacturer Brand, FairPrice and First Choice).

3.6 Survey instrument

In the current study, a questionnaire, consisting of 129 statements, is used to collect data on variables that are hypothesized to provide information on the research topic. In order to attain a non biased result, it has been ensured that the questions asked do not lead the respondents to a certain conclusion, resulting in respondent error. The questionnaire was inspired by those illustrated in previous studies and the results they had generated (e.g. Dodds, Monroe, & Grewal, 1991; Rao & Monroe, 1989) as well as adding some personal input into the topic. Various aspects of the topic were discussed and formed into questions. Further revision into a survey format would be done so that it would be suitable for the current study. A pilot test completed with 15 potential respondents resulted in minor changes.

The questionnaire was divided into five sections. The first section collected demographic data, mostly to be used to categories and compare respondents. They include age, gender, marital status, income level, education, household size and occupation. The second, third, fourth and fifth sections of the questionnaire assessed are based on consumers' perception and preference and their willingness to buy products of the various brands.

Based on the image and information of the display boards, respondent were asked to indicate their agreement with statements on 6-point Likert type scales, anchored by (1) Strongly Disagree and (6) Strongly Agree, where 6 represented the most positive level (Dodds et al., 1991). An even number rating scale was preferred to prevent respondents from providing a neutral or ambivalent answer choice. According to Gwinner (2006), he discovered that neutral answers were rare as in the most of the cases, because only respondents who had a positive or negative experience/opinion would want to participate in a research study. Prototypes from four different product categories, which were used to measure respondents' perception towards the brands, looked exactly the same except for their brand logo. Therefore, in the current studies, respondents would have to be committed to be on either the positive or negative side of the scale when they evaluate the product.

3.7 Reliability Test for questionnaire

The concept of reliability guides the researcher that there shall be the possibility to replicate the results of the research. In order to achieve the reliability of the research, the four threats such as, on the part of the participants, the subject of participant error and subject of participant bias, and on the side of the observer, the observer error and the observer bias will be avoided. To do this, survey questionnaire is planned on the basis of a high measure of structure to minimize biases of the participants and errors coming from the researcher.

Ensuring reliability, Cronbach's alpha was calculated in order to test the reliability of the importance of quality, value and purchase intention of the three brands presented to the consumers. Zhang and Chow (2004) noted that a factor is considered significant if its Cronbach's alpha was 0.70 or above. For the dependent attributes, Cronbach's alpha is tested separately for quality, value and purchase intention. There are a total of 100 items, and the Cronbach's alpha for quality is .965, for value is .835 and for purchase intention, it is .867, all of which means that the items are significant.

3.8 Reliability of the measurement variables

To better understand the characteristics of the respondents, descriptive statistic analysis was used to illustrate the frequency, percentage of the respondents in each demographic variable.
3.8.2 Internal consistency analysis

Coefficient alpha (α) was used to test the internal consistency of each attribute. Robinson and Shaver (1973) pointed out if α is greater than 0.70, it indicates high reliability and if α is smaller than 0.30, then it implies that there is low reliability.
3.8.1 full factorial Conjoint analysiS

The study will use full factorial conjoint analysis to understand respondents' perception and preference towards manufacturer and store brands. The utility value of the stimuli can be used to explain the preference between these combinations.
3.8.2 One way repeat ANOVA
3.8.3 pearson's r correlation coefficient

In the current study, Pearson's correlation coefficient was used to evaluate the linear associations (Creswell, 1994). The linear relationship will then establish their associations, and the basic assessment of the data with regards to the variables and the factors will then be considered (Creswell, 1994).

chapter four: finding and analysis

This chapter of the study covers three sections. The first section is characteristics of respondents, data collection, and pre-test results. The second section exhibits conjoint analysis, ANOVAs, and correlation. Lastly, the third section discusses about the effect of brand names on product evaluation.

4.1 characteristics of respondents

Survey data were analyzed using descriptive statistics of frequency and percentage. For this study, there are 9 demographics questions pertaining to gender, age, status, household size, educational background, occupation and monthly income. There are also questions about the frequency of visit in Fair Price and Cold Storage. Gender is distributed as 56% female and 44% males. When it comes to the age of the respondents, the most belonged in the 26 to 35 years old bracket (33.3%) while the least belonged to the 36 to 45 years old bracket with 20.7%. Marital status is limited into two options as single with 54.7% and married with 45.3%. Further, about 48% of the respondents lived in a household with 4 members and the rest is distributed into living in a household with 2 people (20%), 3 people (16%) and 5 and more people (16%).

Six choices are provided for educational background question including PSLE, O'/N' levels, ITE/ITC, A' levels, diploma degree and master/PhD. Occupation and monthly income are also asked. In terms of employability, respondents were asked whether they are homemakers, students, employed, or retired. The highest responses are working (XXX%) . Moreover, the respondents mostly earn below $1000 (36.7%) and $2000 to $2999 (23.3%). As the study identified two common grocers in Singapore, respondents were asked about the frequency of their visit to Fair Price and Cold Storage. Forty-seven (31.3%) said they are visiting Fair Price on a monthly basis while 38 or 25.3% said on a weekly basis ( =3.13). This is in contrast with the frequency of visit of the respondents to Cold Storage wherein 44.7% of the respondents pay visit on a fortnightly basis ( =3.19). This means that these respondents prefer to pay a visit in Cold Storage every two weeks.

4.2 empirical findings
4.2.1 Pre test Results

To ensure that the all control attributes, especially the products, remain the same in the formal experiment, pre-test study has been conducted on 25th February 2010 with 15 respondents including seven males and eight females. The average age is ranged from 16 to 25. MANOVA was implemented to check the significant difference among the four levels of products (Peanut Butter, Lasagna, Chocolate Bar, and Drinking Yogurt) and other controlled attributes (i.e. prices of the products and weight of the products). Table 1 showed that there is no statistically difference between the products across all of the three dependent attributes (Quality, Value, and Purchase Intention). It signifies that the products are statistically measured as control attributes. With that, it means that the current research can utilize the four products to do further experiment.

4.2.2 Overall reliability of conjoint analysis

Table 2: Part-worth utility scores were generated for each of three dependent attributes. As illustrated in Table 2, the three Pearson's R is 1.00, and the Kendall's tau statistics ranging from .76 to .82, with significance level higher than 95%. Therefore, the result was usable.

4.2.3 Conjoint Analysis: Relative importance of independent attributes

Table 3 displays the average relative importance subjects assigned to each independent attribute (total importance equals 100). The relative importance of the independent attributes shows that brand ranged from 72.71% to 84.71%. These percentages were consistently higher than the other independent attribute. Product ranged from 15.29% to 20.13%, showing that its influence on product evaluation is less impactful.


Hypothesis 2: When assessing with brand cue only, products of manufacturer brands will receive the highest evaluation as compared to those from store brands.

Table5: The first hypothesis (Products of manufacturer brands will receive the highest evaluation as compared to those from store brands) was tested by categorizing the four different products (Peanut Butter, Lasagna, Chocolate Bar and Drinking Yogurt) based on the type of brands (Manufacturer brand, FairPrice and First Choice), and comparing the part-worth means across all the three dependent attributes (Quality, Value, and Purchase Intention).

As shown in Figure 1, the utility score of the three brands remain constant across the dependent attributes. It can be inferred that the participants responded consistently towards the three dependent attributes. With reference to Table 5, analysis of variance tests showed significant effect across the three brands on all dependent attributes; quality F (1.81, 270.51) = 759.68, p < .05, value F (1.44, 215.19) = 759.68, p < .05, and purchase intention F (1.76, 261.92) = 210.00, p < .05. Multiple comparisons were further executed to find out the effect size among the three brands. Across all dependent attributes, Manufacturer brand outscored FairPrice by an average effect size of 3.40, and it also outscored First Choice with an average effect size of 3.28. This result confirms that products of Manufacturer brand, with the highest part-worth utility means consistently across all dependent attributes, received higher evaluation as compared to those from the store brands. Therefore, H1 is supported.

H2: When assessing with brand cue only, products from store brands will receive the same evaluation.

Table 5: The same table (Table 5) was used in order to test the second hypothesis (When assessing with brand cue only, products from store brands will receive the same evaluation). FairPrice and First Choice both possess very similar part-worth utility, which means with no statistically significant differences on all the dependent attributes (Table 5). Although the effect sizes of FairPrice and First Choice range from .07 to .18 (less than .20 Cohen's d value is considered a small effect**), it is interesting to find out that First Choice is constantly rated higher than FairPrice across all dependent attributes. With reference to Figure 1, each of the dependent attribute repeats this pattern between FairPrice and First Choice, although not statistically significant. Nevertheless, the lack of overall statistical differences between the two store brands supports Hypothesis 2.

H3: Perceived value for money of store brands is more strongly correlated with intention to buy store brands than is perceived quality.

The third hypothesis forecasted is that perceived value for money of store brands is more strongly correlated with consumer willingness to buy store brands than its perceived quality. In order to test this hypothesis, the correlation of perceived quality and perceived value for money with purchase intention was calculated across all four products (Richardson et al., 1994). After which, the tests of differences between these dependent correlation were then calculated. With reference to Table X, all Pearson correlations are positive and statically significant. Of which, the correlations of FairPrice is low, definite but with small relationship. Whereas for First Choice, the correlation between perceived quality and purchase intention displays moderate and substantial relationship, and the correlation between perceived value and purchase intention is low, definite but with small relationship (as cited in Bryman, 1997, p.178).

Similar to the findings obtained by Richardson et al. (1994), perceived quality of both FairPrice and First Choice is more strongly associated with purchase intention than is perceived value for money. Therefore, H3 is not supported. Conversely, the results support the opposite of what is forecasted by the hypothesis. That is, consumers generally seem to be more interested in quality than value for money. Even though the findings may have been to a certain degree the results of the task (i.e. consumers did not actually have to purchase the products), these results can provide constructive recommendations in terms of managerial implications. Richardson et al. (1994) commented that a preference for quality as compared to value may imply that positioning store brands as high quality alternatives to manufacturer brands may encourage greater consumer willingness to buy these products.

H3: Product categories will not influence consumers' evaluation on the three attributes.

Table 6: Hypothesis H3 asserts that types of product will have an effect on consumers' evaluation on all three attributes. This hypothesis is tested by grouping three brands together by the types of products and comparing the part-worth means across all three dependent attributes (Table 6). Resulting MANOVA revealed significant effect of the products on the three dependent attributes, including quality F (2.02, 300.16) = 4.73, p < .05, value F (2.83, 421.40) = 9.334, p < .05, and purchase intention F (2.03, 301.97) = 10.07, p < .05. Nevertheless, the multiple comparisons pointed out that not all products are significantly different from each other. Peanut Butter, Chocolate Bar, and Drinking Yogurt exhibited very similar part-worth utility means with no statistical differences. Unexpectedly, Lasagna, with the lowest part-worth utility values across all three dependent attributes, appeared to be significantly different from all other products (Table 6). On average across all dependent attributes, Peanut Butter, Chocolate Bar and Drinking Yogurt scored higher than Lasagna with an effect size of .49, 1.18, .47 respectively.

Although the product category has a significant effect on product evaluation, consumers' evaluation of manufacturer and store brands are still not affected. As shown in Table, when the products evaluations are split up into individual product categories, the evaluation of the brand names still received follows the same pattern (i.e. products of manufacturer brand, with the highest part-worth utility means consistently across all dependent attributes, still received higher evaluation as compared to those from the store brands). This may indicate that brand name have greater impact on product evaluation than is product category. This is also reflected in the importance summary extracted from the conjoint analysis.

Breaking out the age of the respondents into two categories, the resulting MANOVA revealed that younger (16 to 35 years old) and older (36 to 55 years old) respondents have statistically different perceptions toward the four products. According to Table 7, younger respondents perceived all four products categories to have no effect on the evaluation of products. These results are statistically similar to the results obtained from the pre-test, where respondents also belong to the same age group. In the case of older respondents, the effect of the four product categories on product evaluation was statistically significant. With further investigation, the multiple comparisons demonstrated that Lasagna, with consistently lowest part-worth utility means, was the least preferred product by the older respondents across all three dependent attributes.

Hypothesis 4: The evaluation of brand names varies depends on the different demographics.

In order to test if the evaluation of brand names varies depends on different demographics, H4 was tested by categorizing the four different products based on the type of brands, and comparing the part-worth means across all the three dependent attributes (Quality, Value, and Purchase Intention) according to different demographics. According to Table, the findings reveal that there is no significant difference in the evaluation of brand names among the demographics. Products of manufacturer brand, with the highest evaluation across all three dependent, are perceived to be of superior than products of store brand products by respondents from all demographics. Pair comparison also showed that products of FairPrice and First Choice, that possess very similar utility scores, are significant the same.

4.2 Analysis

As mentioned, the one of the aims was to examine Singapore consumers' perception towards manufacturer and store brands across specific product categories. Regardless of product categories (Peanut Butter, Lasagna, Chocolate Bar and Drinking Yogurt), the research findings demonstrated that manufacturer brand has received the highest evaluation as compared to FairPrice and First Choice across all three attribute (quality, value, and purchase intention). This result is in line with what previous studies discovered; consumers still prefer manufacturer brands over store brands, if the price is right (Shapiro, 1993). Furthermore, the findings also indicate that consumers' unfavorable reactions to store brand products are largely the result of consumers' propensity to rely on brand cue when assessing product performance. For example, despite of same price manipulated in each product category, the evaluation of manufacturer brand received significantly more favorable quality assessment than store brands. The value of products had less impact.

This pattern can be explain that the context of price and perceive quality relationship (Monroe & Dodds, 1988; Olson, 1976) is not used when consumers evaluate product performance in the current experiment. According to the theory, higher-priced products are believed to be of higher quality. In reality, store brands, which are approximately 10% to 30% cheaper than manufacturer-brands in the grocery product classes, are perceived to be of lower quality (Baltas, 1997). In this case, although products of manufacturer brand, FairPrice and First Choice possess the same price, consumers still evaluate the quality of the product base on brands. Again, this emphasizes that effect of brand names has a great impact when assessing product.

When it comes to the comparison between store brands, the research finding could not identify a statistically significant difference between FairPrice and First Choice. With very similar marketing and positioning strategies between FairPrice (meet the needs of consumers who want quality products at affordable prices) and First Choice (a name you can trust for quality and value), the results reveals that consumers statistically perceived both store brands to be the same. Despite that, it is interesting to find out that First Choice is constantly rated higher than FairPrice across all dependent attributes, although there is no significant difference. Although these findings may have been to some degree the results of the misinterpretation (i.e. consumers may not actually notice the difference in marketing and positioning strategy between the two store brands), the results are inspirational in term of managerial implications. The same perception towards the store brands may suggest that repositioning FairPrice or First Choice may induce greater difference in perception between the store brands.

Correlation evidence revealed an opposite result of what is predicted by hypothesis H3 (Perceived value for money of store brands is more strongly correlated with intention to buy store brands than is perceived quality). The findings suggested that consumers by and large seem to be more attracted to quality than value for money when buying store brand products. This can be supported by previous studies, where perceived quality was found to have a positive direct effect on purchase intention (Carman, 1990; Boulding et al., 1993; Parasuraman et al., 1996), while value did not possess any significant effect (direct or indirect) on purchase intentions (Rodula, 1995). In short, consumers' purchase intention will not be affect by the value. However, when the perceived quality of a product is high, consumers are more likely to purchase it. Nevertheless, Richardson et al. (1994) pointed out that store brands (e.g. FairPrice and First Choice) that position as high-quality brands and use a value for money marketing approach may be signaling “lower quality for lower prices” instead of “very good quality for lower prices” as hoped. This suggests that retailers' value for money promotion efforts may not be effective in solving problems associated with the poor perceived quality of store brands.

When the four types of product categories were test for similarity, the unexpected results reveal that Lasagna was significant different from the other three products (Peanut Butter, Chocolate Bar, and Drinking Yogurt). Despite of product category having a significant effect on product evaluation, consumers' evaluation of manufacturer and store brands are still not affected (i.e. products of manufacturer brand, with the highest part-worth utility means consistently across all dependent attributes, still received higher evaluation as compared to those from the store brands). With further investigation, the respondents are categorized into two age groups. The younger group (16 to 35 years old) of respondents perceived all four products categories to have no effect on the evaluation of products. In the case of older (36 to 55 years old) respondents, Lasagna was the least preferred product across all three dependent attributes. From the current experiment, it can be inferred that generally older respondents' acceptance level of Lasagna is statistically lower than the younger respondents. The result was not surprising as it was supported by previous studies that have identified difference in food shopping and consumption behaviors between the age groups. According to Hunter and Worsley (2009), older adults appear to perceive convenience foods negatively. In addition, a study on older people's intentions to eat convenience foods across eight European countries discovered that intentions to consumer convenience foods were very low (Saba, Messina, Turrini, Lumbers, & Raats, 2008). According to these researchers, the possible reasons for older people's low acceptance level of convenience foods were due to low perceived need and low perceived social pressure to eat these foods. Further evidences revealed that people born between 1965 to 2007 have many other demands on their time and therefore tend to consume convenience foods and ready-made meal. On the other hand, baby boomers and older adults may have more time for food preparation and be more repentance to consume ready-made meal (as cited in Hunter & Worsley, 2009). Despite the older respondents' low acceptance level of Lasagna, the results are useful in providing useful managerial implications to retailers. Basically, if retailers will to launch Lasagna in the local market, their marketing plans should focus on the younger consumers.

Last but not least, for store brand proneness in terms of demographics variables, the current research found that there is no difference as to how consumers from various demographics perceive manufacturer and store brands. Consumer, in general, felt more positive towards manufacturer brands than store brands. These findings contradicts a number of previous studies (Burger & Schott, 1972); (Frank & Boyd, 1965), and point out that social-economic and demographics variables are insufficient to distinguish consumers' proneness to products of manufacturers and store brands. Nevertheless, like many studies before (for example, Myers, 1967; Dick et al., 1995; Burton et al., 1998), the findings reveals that consumers from all demographics perceive retailers' and manufacturers' products differently.

Chapter five: conclusion and recommendations

Branding of products will never run out of criticisms. However, as long as it helps the market cater to the needs of the consumers, particularly that of our need for product information, then it is still well within the boundaries of product branding. The focus of this study to is to determine the difference of perception of consumers pertaining to manufacturer and supermarket retailers' brand.

5.1 Research findinds


The current study has a few limitations that should be acknowledged. The first of these limitations stems from the use of a convenience sample. The data were collected outside shopping centres and supermarkets located at the north of Singapore. Moreover, the sample size of 150 was also relative small to represent the whole population. Therefore, the sample may not be representative of entire Singaporean consumer population and their perception and preference towards manufacturer and store brands.

Another limitation arose from the use of products categories in the current study. As the full factorial design was adopted to generate the current findings, the conjoint methods contain a few limitations in the current experiment. Respondents were asked to observe 12 (three brands x four products) display boards and rate their perception score after examining each display board. The average time to complete the experiment was 20 minutes. Hence, it may challenge the endurance for general public, increase respondents' tendency to rush through the survey, and ultimately affect results collected.

Finally, all four product categories adopted by the current study belong to the food categories. Furthermore, the mock up of the products presented to respondents were design by business student with little experience in design. Therefore, they may not be the ideal products to determine consumers' perception of manufacturer and store brands. As such, these results may not apply to other